Comparative study of the whisky aroma profile based on headspace solid phase microextraction using different fibre coatings

A dynamic headspace solid-phase microextraction (HS-SPME) and gas chromatography coupled to ion trap mass spectrometry (GC–ITMS) method was developed and applied for the qualitative determination of the volatile compounds present in commercial whisky samples which alcoholic content was previously adjusted to 13% (v/v). Headspace SPME experimental conditions, such as fibre coating, extraction temperature and extraction time, were optimized in order to improve the extraction process. Five different SPME fibres were used in this study, namely, poly(dimethylsiloxane)(PDMS),poly(acrylate)(PA),Carboxen-poly(dimethylsiloxane)(CAR/PDMS),Carbowax-divinylbenzene(CW/DVB)and Carboxen-poly(dimethylsiloxane)-divinylbenzene (CAR/PDMS/DVB). The best results were obtained using a 75 m CAR/PDMS fibre during headspace extraction at 40◦C with stirring at 750rpm for 60min, after saturating the samples with salt. The optimised methodology was then appliedtoinvestigatethevolatilecompositionprofileofthreeScotchwhiskysamples—BlackLabel,BallantinesandHighlandClan.Approximately seventy volatile compounds were identified in the these samples, pertaining at several chemical groups, mainly fatty acids ethyl esters, higher alcohols, fatty acids, carbonyl compounds, monoterpenols, C13 norisoprenoids and some volatile phenols. The ethyl esters form an essential group of aroma components in whisky, to which they confer a pleasant aroma, with “fruity” odours. Qualitatively, the isoamyl acetate, with “banana” aroma,wasthemostinteresting.Quantitatively,significantcomponentsareethylestersofcaprilic,capricandlauricacids.Thehighestconcentration of fatty acids, were observed for caprilic and capric acids. From the higher alcohols the fusel oils (3-methylbutan-1-ol and 2.phenyletanol) are the most important ones.

Effectiveness of different solid-phase microextraction fibres for differentiation of selected Madeira island fruits based on their volatile metabolite profile: identification of novel compounds

A headspace solid-phase microextraction (HS-SPME) procedure based on five commercialised fibres (85 μm polyacrylate – PA, 100 μm polydimethylsiloxane – PDMS, 65 μm polydimethylsiloxane/divinylbenzene – PDMS/DVB, 70 μm carbowax/divinylbenzene – CW/DVB and 85 μm carboxen/polydimethylsiloxane – CAR/PDMS) is presented for the characterization of the volatile metabolite profile of four selected Madeira island fruit species, lemon (Citrus limon), kiwi (Actinidia deliciosa), papaya (Carica papaya L.) and Chickasaw plum (Prunus angustifolia). The isolation of metabolites was followed by thermal desorption gas chromatography–quadrupole mass spectrometry (GC–qMS) methodology. The performance of the target fibres was evaluated and compared. The SPME fibre coated with CW/DVB afforded the highest extraction efficiency in kiwi and papaya pulps, while in lemon and plum the same was achieved with PMDS/DVB fibre. This procedure allowed for the identification of 80 compounds, 41 in kiwi, 24 in plums, 23 in papaya and 20 in lemon. Considering the best extraction conditions, the most abundant volatiles identified in kiwi were the intense aldehydes and ethyl esters such as (E)-2-hexenal and ethyl butyrate, while in Chicasaw plum predominate 2-hexenal, 2-methyl-4-pentenal, hexanal, (Z)-3-hexenol and cyclohexylene oxide. The major compounds identified in the papaya pulp were benzyl isothiocyanate, linalool oxide, furfural, hydroxypropanone, linalool and acetic acid. Finally, lemon was shown to be the most divergent of the four fruits, being its aroma profile composed almost exclusively by terpens, namely limonene, γ-terpinene, o-cymene and α-terpinolene. Thirty two volatiles were identified for the first time in the fruit or close related species analysed and 14 volatiles are reported as novel volatile metabolites in fruits. This includes 5 new compounds in kiwi (2-cyclohexene-1,4-dione, furyl hydroxymethyl ketone, 4-hydroxydihydro-2(3H)-furanone, 5-acetoxymethyl-2-furaldehyde and ethanedioic acid), 4 in plum (4-hydroxydihydro-2(3H)-furanone, 5-methyl-2-pyrazinylmethanol, cyclohexylene oxide and 1-methylcyclohexene), 4 in papaya (octaethyleneglycol, 1,2-cyclopentanedione, 3-methyl-1,2-cyclopentanedione and 2-furyl methyl ketone) and 2 in lemon (geranyl farnesate and safranal). It is noteworthy that among the 15 volatile metabolites identified in papaya, 3-methyl-1,2-cyclopentanedione was previously described as a novel PPARγ (peroxisome proliferator-activated receptor γ) agonist, having a potential to minimize inflammation.

Dynamic headspace solid-phase microextraction combined with one-dimensional gas chromatography–mass spectrometry as a powerful tool to differentiate banana cultivars based on their volatile metabolite profile

In this study the effect of the cultivar on the volatile profile of five different banana varieties was evaluated and determined by dynamic headspace solid-phase microextraction (dHS-SPME) combined with one-dimensional gas chromatography–mass spectrometry (1D-GC–qMS). This approach allowed the definition of a volatile metabolite profile to each banana variety and can be used as pertinent criteria of differentiation. The investigated banana varieties (Dwarf Cavendish, Prata, Maçã, Ouro and Platano) have certified botanical origin and belong to the Musaceae family, the most common genomic group cultivated in Madeira Island (Portugal). The influence of dHS-SPME experimental factors, namely, fibre coating, extraction time and extraction temperature, on the equilibrium headspace analysis was investigated and optimised using univariate optimisation design. A total of 68 volatile organic metabolites (VOMs) were tentatively identified and used to profile the volatile composition in different banana cultivars, thus emphasising the sensitivity and applicability of SPME for establishment of the volatile metabolomic pattern of plant secondary metabolites. Ethyl esters were found to comprise the largest chemical class accounting 80.9%, 86.5%, 51.2%, 90.1% and 6.1% of total peak area for Dwarf Cavendish, Prata, Ouro, Maçã and Platano volatile fraction, respectively. Gas chromatographic peak areas were submitted to multivariate statistical analysis (principal component and stepwise linear discriminant analysis) in order to visualise clusters within samples and to detect the volatile metabolites able to differentiate banana cultivars. The application of the multivariate analysis on the VOMs data set resulted in predictive abilities of 90% as evaluated by the cross-validation procedure.